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Activity Number:
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407
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 1, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Business and Economics Statistics Section
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| Abstract - #310133 |
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Title:
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Seasonal Heteroscedasticity in Time Series: Modeling, Estimation, and Testing
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Author(s):
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William R. Bell*+ and Thomas M. Trimbur
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Companies:
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U.S. Census Bureau and Federal Reserve Board
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Address:
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SRD, Room 5K142A, Washington, DC, 20233-9100,
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Keywords:
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seasonal ARIMA model ; state space model ; seasonal adjustment
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Abstract:
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Seasonal heteroscedasticity refers to regular changes in variability over the calendar year. Models for two different forms of seasonal heteroscedasticity were recently proposed by Proietti (2004) and Bell (2004). We examine use of likelihood ratio tests with the models to test for the presence of seasonal heteroscedasticity, and use of model comparison statistics (AIC) to compare the models and to search among alternative patterns of seasonal heteroscedasticity. We apply the models and tests to U.S. Census Bureau monthly time series of housing starts and building permits, and to time series of Industrial Production Indexes from the Federal Reserve Board.
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